1. Field of the Invention
This invention relates generally to semiconductor manufacturing, and, more particularly, to a method and apparatus for performing generating binary data from continuous data for performing automated analysis routines.
2. Description of the Related Art
The technology explosion in the manufacturing industry has resulted in many new and innovative manufacturing processes. Today's manufacturing processes, particularly semiconductor manufacturing processes, call for a large number of important steps. These process steps are usually vital, and therefore, require a number of inputs that are generally fine-tuned to maintain proper manufacturing control.
The manufacture of semiconductor devices requires a number of discrete process steps to create a packaged semiconductor device from raw semiconductor material. The various processes, from the initial growth of the semiconductor material, the slicing of the semiconductor crystal into individual wafers, the fabrication stages (etching, doping, ion implanting, or the like), to the packaging and final testing of the completed device, are so different from one another and specialized that the processes may be performed in different manufacturing locations that contain different control schemes.
Generally, a set of processing steps is performed across a group of semiconductor wafers, sometimes referred to as a lot. For example, a process layer that may be composed of a variety of different materials may be formed across a semiconductor wafer. Thereafter, a patterned layer of photoresist may be formed across the process layer using known photolithography techniques. Typically, an etch process is then performed across the process layer using a patterned layer of photoresist as a mask. This etching process results in the formation of various features or objects in the process layer. Such features may be used as, for example, a gate electrode structure for transistors. Many times, trench isolation structures are also formed across the substrate of the semiconductor wafer to isolate electrical areas across a semiconductor wafer. One example of an isolation structure that can be used is a shallow trench isolation (STI) structure.
The manufacturing tools within a semiconductor manufacturing facility typically communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface to which a manufacturing network is connected, thereby facilitating communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script, which can be a software program that automatically retrieves the data needed to execute a specific manufacturing process.
FIG. 1 illustrates a typical semiconductor wafer 105. The semiconductor wafer 105 typically includes a plurality of individual semiconductor die 103 arranged in a grid 150. Using known photolithography processes and equipment, a patterned layer of photoresist may be formed across one or more process layers that are to be patterned. As part of the photolithography process, an exposure process is typically performed by a stepper on single or multiple die 103 locations at a time, depending on the specific photomask employed. The patterned photoresist layer can be used as a mask during etching processes, wet or dry, performed on the underlying layer or layers of material, e.g., a layer of polysilicon, metal or insulating material, to transfer the desired pattern to the underlying layer. The patterned layer of photoresist is comprised of a plurality of features, e.g., line-type features or opening-type features that are to be replicated in an underlying process layer.
Turning now to FIG. 2, a flowchart depiction of a prior art process flow is illustrated. A manufacturing system may process one or more semiconductor wafers (block 210). Upon processing the wafer, the manufacturing system may acquire metrology data relating to the processing of the wafers (block 210). For further analysis of the metrology data, the manufacturing system may store the acquired metrology data (block 230). The manufacturing system may continue to process additional wafers (block 240). Upon processing of the additional wafers, metrology data relating to the subsequently processed wafers may be acquired and stored (block 250). Based on the accumulated metrology data, a standard deviation analysis may be performed (block 250). This process may include analyzing various characteristics (e.g., as metrology information, speed grades, etc.,) relating to the quality of the processed die. The standard deviation analysis provides for a continuous data stream that provides indications of the characteristics of various portions of a plurality of wafers. Even binary-type data, (e.g., whether a particular wafer region passes a test or not), may become an analog-style continuous signal when analyzing data relating to several wafers. Accordingly, state-of-the-art systems provide an analog, continuous type data relating the characteristics of the die of various wafers. Analyzing this type of data relating to a plurality of wafers to identify a problem region across several wafers is difficult. State-of-the-art standard deviation analysis does not provide efficient multi-wafer data analysis since each analysis of a portion of several wafers provides many different results that are difficult to quantify as a single data representation. Therefore, analysis of multiple wafer data sets for identifying a common problem area across several wafers may be inefficient and cumbersome when using state-of-the-art technology.
The present invention is directed to overcoming, or at least reducing, the effects of one or more of the problems set forth above.